This scoping review was conducted in accordance with the methodological framework proposed by Arksey and O’Malley [35], following their 5-stage approach. The review was reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines [36]. The completed PRISMA-ScR checklist is provided in Checklist 1. The study protocol and analysis plan were prospectively registered on the Open Science Framework [37].

This scoping review aimed to systematically map the current evidence on digital health technologies to support mobility recovery among ICU survivors. The review addressed the following research questions: (1) What digital health technologies have been applied to support mobility recovery among ICU survivors? (2) Which dimensions of mobility are targeted by these digital health technologies? (3) What evidence exists regarding mobility-related outcomes, implementation experiences, and user perspectives associated with these digital health technologies?

The eligibility criteria were developed according to the PCC (population, concept, and context) framework [38].

The updated database searches identified 2557 records. After the removal of 1291 duplicates, 1266 records underwent title and abstract screening, of which 906 were excluded. Full texts were sought for 360 reports; 5 could not be retrieved, leaving 355 reports for eligibility assessment. Of these, 328 were excluded because of an ineligible study design (n=81), an ineligible population (n=85), the absence of an eligible digital health intervention (n=64), or the absence of a mobility-related outcome (n=98). Ultimately, 27 reports representing 24 unique parent studies were included in the review. The study selection process is presented in the PRISMA flow diagram (Figure 1).

The review included 27 reports representing 24 unique parent studies, comprising 11 randomized trial reports [39-49], 9 nonrandomized quantitative reports [50-58], 3 qualitative reports [59-61], 2 case reports [62,63], 1 innovation report [64], and 1 multiple methods report [65]. Reports arising from the same parent study were linked and retained when they contributed distinct evidence; each parent study was counted once in the total number of unique studies. The 3 pairs of linked reports were O’Neill et al [44] and Ghiglieri et al [61], Kovaleva et al [59] and Boehm et al [49], and Rose et al [64] and Apps et al [65].

The studies were conducted across diverse geographical settings and included survivors of COVID-19–related critical illness [39-41,43,45,47,51-53,55,62], acute respiratory failure [42,48,54], sepsis and/or acute respiratory distress syndrome [46,49,59], prolonged mechanical ventilation [44,50,61,65], and broader post-ICU populations [48,56-58,60], as well as a survivor of severe burn injury requiring prolonged critical care [63]. Participant characteristics and age were reported heterogeneously across studies. Basic study characteristics are summarized in Table 2, while detailed information on the study populations, digital health technologies, intervention components, duration, delivery format, providers, settings, and mobility-related outcomes is provided in Table S1 in Multimedia Appendix 1.

Statistical and analytical approaches varied across study designs, ranging from descriptive and conventional group comparisons to adjusted regression, mixed-effects, and longitudinal or clustered models; qualitative studies used content, thematic, or framework-based analyses [40,42,44,48,59,61]. Reported handling of home-generated digital data included synchronization checks, wear-time or data-completeness criteria, exclusion of insufficient observations, and aggregation across valid monitoring periods [39,40,53,56-58], whereas explicit signal-level filtering or cross-device calibration was rarely reported. Detailed study-level information is provided in Table S2 in Multimedia Appendix 1.

Evidence on feasibility, safety, adherence, usability, acceptability, and user experience was synthesized separately from clinical outcome evidence. Across the included reports, these outcomes were assessed using measures of recruitment and retention, intervention completion and adherence, safety, usability and satisfaction, and qualitative accounts of user experience and implementation barriers.

Feasibility, safety, adherence, and implementation outcomes were synthesized separately from clinical effectiveness findings (Table S4 in Multimedia Appendix 1). Several interventions reported favorable engagement or completion, although substantial variation was observed across studies. Remote multicomponent rehabilitation achieved full adherence in 73.2% (169/231) of participants, with 88.7% (205/231) attending at least one session [44], while virtual post-ICU rehabilitation showed 73.6% (28/38) retention and 82% (23/28) adherence [52]. Wearable-monitoring studies demonstrated the feasibility of collecting home activity data, but incomplete device use, technical failures, and missing data reduced data completeness [53,56,58]. In the multicenter stepped-wedge trial, among 300 eligible intervention patients, 269 (89.7%) attended at least 1 ward session and 222 (74.0%) attended at least 1 postdischarge session [48]. Thus, digital interventions were generally deliverable, but sustained participation and completeness of remotely generated data remained variable.

Acceptability and user experience findings were generally favorable but were interpreted separately from clinical effectiveness (Table S5 in Multimedia Appendix 1). Remote multicomponent rehabilitation received higher acceptability ratings than standard care [44], while a mobile app prototype achieved median System Usability Scale scores of 76 among ICU survivors and 88 among caregivers [54]. ICU-specific VR was associated with higher satisfaction with ICU aftercare [47], and favorable satisfaction or acceptability was also reported for app-based rehabilitation, immersive VR, telemedicine recovery clinics, and digital recovery platforms [49,57,63,65]. Qualitative findings highlighted individualized support, continuity of care, reassurance, and professional access as facilitators, whereas technical burden, limited digital access, and insufficient personalization were recurrent barriers [59,61,65].

This scoping review mapped the use of digital health technologies to support mobility recovery among ICU survivors across 7 technology categories. Interventions most commonly incorporated exercise-based rehabilitation, alongside monitoring, education, self-management support, and remote follow-up. Mobility outcomes were heterogeneous and concentrated on body functions and activity-level performance, with comparatively limited attention to participation. Although feasibility and acceptability were generally favorable when assessed, evidence of clinical effectiveness remained mixed, and long-term implementation data were limited.

A notable finding of this review was that telemedicine and telerehabilitation were the most frequently adopted digital health technologies. This predominance may reflect the substantial and persistent rehabilitation needs of ICU survivors, who commonly experience long-term physical impairment, reduced exercise capacity, respiratory dysfunction, and difficulties accessing postdischarge rehabilitation services [66-68]. Digital technologies offer an opportunity to extend rehabilitation beyond hospital settings and provide continuous support throughout the recovery trajectory [69]. In addition to improving access to rehabilitation, remote and telehealth-based approaches may reduce geographical and transportation barriers, facilitate continuity of care after hospital discharge, enable timely monitoring of recovery, and strengthen patient self-management in home settings, where access to structured post-ICU rehabilitation is often limited.

The COVID-19 pandemic further accelerated the adoption of remote rehabilitation technologies. Eleven of the 24 (45.8%) included studies focused on survivors of COVID-19–related critical illness, reflecting the urgent demand for scalable rehabilitation strategies during a period when infection-control measures substantially restricted conventional outpatient and community-based rehabilitation services. At the same time, the rapid expansion of telehealth infrastructure and increasing familiarity with digital health care delivery further facilitated the implementation of remote rehabilitation programs. Together, these factors contributed to the widespread use of telemedicine and telerehabilitation for supporting patients with persistent physical and respiratory impairments following severe COVID-19 [70].

However, the predominance of COVID-19–related studies should be considered when interpreting the current evidence. Compared with general ICU survivors, individuals recovering from COVID-19 may experience distinct recovery patterns, particularly persistent respiratory symptoms, postviral fatigue, and impaired exercise tolerance, which may influence both rehabilitation needs and responses to digital intervention [71,72]. In contrast, evidence involving non-COVID ICU populations, such as survivors of sepsis, acute respiratory failure, prolonged mechanical ventilation, and other critical illnesses, remains relatively limited. Furthermore, many COVID-19–related digital programs were rapidly developed during the pandemic and were commonly evaluated over short intervention periods, with limited evidence regarding their long-term sustainability and integration into routine post-ICU care [70,73]. Beyond these population-specific considerations, successful implementation of remote rehabilitation also depends on patients’ digital literacy, access to internet-enabled devices, reliable connectivity, and, in some cases, caregiver support. These factors may influence patient engagement, equity of access, and the scalability of digital rehabilitation programs in routine clinical practice.

Exercise-based rehabilitation emerged as the most frequently reported functional component among the included digital health technologies. This finding is unsurprising given that persistent physical impairments, including muscle weakness, reduced exercise tolerance, and limitations in physical functioning, are among the most common consequences experienced by ICU survivors after critical illness. Previous studies have shown that these impairments may persist for months or even years after hospital discharge and contribute to long-term disability, reduced health-related quality of life, and difficulties returning to previous life roles [22-24,74]. Consequently, exercise rehabilitation remains a cornerstone of post-ICU recovery programs and is strongly recommended to mitigate long-term physical disability and promote functional restoration [75]. This predominance may also reflect the characteristics of current digital health technologies, as exercise programs are more readily delivered through telehealth platforms, and their outcomes can be objectively monitored using wearable devices and standardized performance measures. By contrast, broader domains such as social participation and community reintegration are less amenable to remote measurement and digital monitoring.

However, the predominance of exercise-centered technologies highlights an important gap in current digital rehabilitation strategies. Mobility recovery after critical illness is increasingly recognized as a multidimensional process encompassing body functions and structures, activities, and participation [14,76-78]. Consistent with the findings of this review, existing digital health technologies primarily addressed body functions and activity-level performance, particularly exercise capacity, muscle strength, and functional performance, while participation outcomes were less frequently assessed. Therefore, future digital health technologies should move beyond physical rehabilitation alone and incorporate more comprehensive, person-centered recovery goals.

Furthermore, although digital technologies offer opportunities for continuous monitoring and personalized rehabilitation, current apps largely remain tools for remote delivery and assessment rather than adaptive rehabilitation systems. Future integration of wearable sensing, AI, and real-time feedback may facilitate closed-loop rehabilitation models that dynamically tailor interventions according to patients’ changing recovery needs [79,80].

Beyond conventional telemedicine and telerehabilitation, emerging digital technologies included VR, rehabilitation robots, wearable activity monitoring, and digital recovery platforms. Current evidence for these technologies was predominantly derived from feasibility, pilot, and observational studies, with generally favorable feasibility and user experience findings when assessed. However, evidence of clinical effectiveness remained limited and inconsistent. VR-based rehabilitation was perceived as enjoyable and feasible among ICU survivors, with no serious adverse events reported [50]. App-based and video-supported rehabilitation programs also reported favorable adherence and retention, supporting their implementation feasibility rather than establishing clinical effectiveness [40,52]. In addition, digital recovery platforms and virtual follow-up services were valued for facilitating access to information, self-management, and communication with health care professionals [54,59,60,64].

However, the current evidence primarily reflects early-stage implementation, as many emerging digital technologies were evaluated in feasibility studies, pilot trials, or small observational studies with relatively short follow-up periods. Although several studies reported favorable usability and acceptability through satisfaction questionnaires, usability scales, or qualitative interviews, a comprehensive understanding of long-term user engagement and implementation barriers remains limited. Future development of digital rehabilitation technologies should therefore adopt more patient-centered approaches, including co-design involving ICU survivors and caregivers, as well as mixed methods evaluations that integrate quantitative usability measures with qualitative exploration of user experiences. In addition, successful implementation will require attention to data privacy and security, integration into routine clinical care, and adequate training and support for health care professionals. Such considerations may help ensure that emerging digital technologies are not only technically feasible but also meaningful, accessible, and sustainable in supporting long-term recovery after critical illness.

Another important finding of this review was the substantial heterogeneity in mobility assessment and outcome measurement. Most studies focused on basic physical capacity and functional performance, commonly assessed using the 6MWT, sit-to-stand tests, handgrip strength, the Timed Up and Go test, and other performance-based measures [39-41,43-45,51,52,55,62]. Although these outcomes are clinically meaningful for evaluating physical recovery after critical illness, they capture only part of the multidimensional nature of mobility.

Measures addressing broader activity and participation outcomes were less frequently reported, including functional independence [43,62], ADLs, activity participation, and mobility- or participation-related recovery goals [42,43,54,60,62,64]. This imbalance suggests that current digital health research has predominantly evaluated mobility through body functions and activity-level performance rather than across the full spectrum of post-ICU functioning.

The heterogeneity of outcome measurement remains a major challenge for comparing and synthesizing evidence across digital rehabilitation studies. The PRACTICE (Physical Rehabilitation Core Outcomes in Critical Illness) core outcome set provides a framework to promote standardized reporting of physical rehabilitation outcomes in critically ill populations [81]. However, as digital health interventions increasingly extend beyond exercise training to include remote monitoring, self-management, and long-term recovery support, future research should combine standardized core outcomes with broader multidimensional assessments that reflect independence, participation, and patient-centered recovery trajectories. Analytical approaches were also heterogeneous, ranging from descriptive and unadjusted comparisons to adjusted regression, mixed-effects, and longitudinal or clustered models. This variation reflected differences in study design but also limited the comparability of effect estimates across studies. Future studies should prespecify analytical strategies appropriate to repeated and longitudinal measurements and consistently report effect estimates with measures of uncertainty.

The handling of home-generated digital data was also inconsistently reported. Reported approaches included synchronization checks, wear-time or data-completeness thresholds, exclusion of insufficient observations, aggregation across valid monitoring periods, and missing-data assessment, whereas explicit signal-level artifact filtering and cross-device calibration were rarely described. Future studies should prespecify device validation, valid-wear and nonwear criteria, data-cleaning procedures, and missing-data handling to improve the reproducibility and interpretability of remotely generated data.

Several implications for future research emerged from this review. First, more adequately powered randomized controlled trials with longer follow-up periods are needed to establish the long-term effectiveness and sustainability of digital health technologies, given that mobility recovery after critical illness is a prolonged and dynamic process. Second, future studies should move beyond short-term physical outcomes and incorporate multidimensional recovery indicators, including independence in ADLs, community and social participation, return to occupational or caregiving roles, patient-reported physical function, and individualized mobility- or participation-related recovery goals. Third, theoretical foundations were infrequently and inconsistently reported; future interventions would benefit from clearly articulated behavioral or rehabilitation frameworks where appropriate. Finally, future research should consider implementation factors, including digital literacy, technology accessibility, caregiver involvement, and health equity, to support broader adoption in ICU survivorship care.

This review has several strengths. A comprehensive search strategy was applied, and evidence was synthesized across technology types, delivery models, intervention components, and mobility-related outcomes. The review also identified important gaps in outcome measurement, theoretical grounding, and implementation evidence.

Several limitations should be acknowledged. First, although 27 reports representing 24 unique parent studies were included, many were feasibility, pilot, qualitative, or small observational studies, limiting conclusions regarding clinical effectiveness. Second, substantial heterogeneity in populations, interventions, outcome measures, and analytical approaches limited direct comparisons across studies. Third, a substantial proportion of the evidence was derived from survivors of COVID-19–related critical illness, which may limit generalizability to the broader ICU survivor population. In addition, classifying multicomponent interventions according to their predominant digital function may have simplified the overlap between technology categories. Finally, no formal methodological quality or risk-of-bias appraisal was conducted; therefore, differences in study quality were not incorporated into the synthesis, and findings regarding clinical effectiveness should be interpreted cautiously.

Digital health technologies have been applied across diverse approaches to support mobility recovery among ICU survivors, with telemedicine and telerehabilitation being the most frequently used. Current evidence predominantly addresses body functions and activity-level performance, with limited attention to participation. Although feasibility and acceptability were generally favorable, evidence of clinical effectiveness remains inconsistent, highlighting the need for rigorous longitudinal studies using multidimensional, patient-centered mobility outcomes.